Results

Products

One of the main aims of the project is to create and operate a computer based modelling environment. The following models and online virtual environments are all part of the project results.

Website of the Biome-BGCMuSo model (called BBGC-MAg in the project)

Source code of Biome-BGCMuSo v5 on GitHub

The Biome-BGC Projects Database & Management System [BBGCDB]

The Biome-BGC Projects Database & Management System v5.0 [with BBBC-Mag 1.0 implementation]

RBBGCMuso software package [supports the easy application of Biome-BGCMuSo in R environment, execution of sensitivity-studies, etc.]

Technical note: Sensitivity analysis of Biome-BGCMuSo using RBBGCMuso

"Introduction to the AgroMo modelling framework" workshop flyer

Publications

Barcza, Z. and Fodor, N. [eds.] 2018. The AgroMo approach: development of an integrated biogeochemical-crop model system in Hungary - synergy and cooperation of the model and the observations. Detailed description about AgroMo (available only in Hungarian)

Fodor, N., Challinor, A., Droutsas, I., Ramirez-Villegas, J., Zabel, F., Koehler, A.K., Foyer, C.H., 2017. Integrating Plant Science and Crop Modeling: Assessment of the Impact of Climate Change on Soybean and Maize Production. Plant Cell Physiol. 58, 1833-1847. doi:10.1093/pcp/pcx141

Göndöcs, J., Breuer, H., Pongrácz, R., Bartholy, J., 2017. Urban heat island mesoscale modelling study for the Budapest agglomeration area using the WRF model. Urban Clim. 21, 66-86. doi:10.1016/j.uclim.2017.05.005

Haszpra, L., Hidy, D., Taligás, T., Barcza, Z., 2018. First results of tall tower based nitrous oxide flux monitoring over an agricultural region in Central Europe. Atmospheric Environment 176, 240-251. doi:10.1016/j.atmosenv.2017.12.035

Kern, A., Marjanović, H., Dobor, L., Anić, M., Hlásny, T., Barcza, Z., 2017. Identification of Years with Extreme Vegetation State in Central Europe Based on Remote Sensing and Meteorological Data. South-east European forestry (SEEFOR), 8, 1-20. doi: https://doi.org/10.15177/seefor.17-05

Kis, A., Pongrácz, R., Bartholy, J., Szabó, J.A., 2017. Application of RCM results to hydrological analysis. Időjárás - Q. J. Hungarian Meteorol. Serv. 121, 437-–452.

Mackei, M., Barcza, Z., Péntek, G., Gábor, Gy., Reibling, T., Solymosi, N., 2017. Kárpát-medencei hőstressz-előrejelzési rendszer. Magyar Állatorvosok Lapja (Hungarian Veterinary Journal), 139, 337-343.

Ostrogović Sever, M.Z., Paladinić, E., Barcza, Z., Hidy, D., Kern, A., Anić, M., Marjanović, H., 2017. Biogeochemical Modelling vs. Tree-Ring Measurements - Comparison of Growth Dynamic Estimates at Two Distinct Oak Forests in Croatia. South-east European forestry (SEEFOR) 8, 71-84. doi: 10.15177/seefor.17-17

Salma, I., Németh, Z., Weidinger, T., Maenhaut, W., Claeys, M., Molnár, M., Major, I., Ajtai, T., Utry, N., Bozóki, Z., 2017. Source apportionment of carbonaceous chemical species to fossil fuel combustion, biomass burning and biogenic emissions by a coupled radiocarbon-levoglucosan marker method. Atmos. Chem. Phys. 17, 13767-13781. doi:10.5194/acp-17-13767-2017

Bartholy, J., Pongrácz, R., 2018. A brief review of health-related issues occurring in urban areas related to global warming of 1.5°C. Curr. Opin. Environ. Sustain. 30, 123-132. doi:10.1016/j.cosust.2018.05.014

Enroth, J., Mikkilä, J., Németh, Z., Kulmala, M., and Salma, I., 2018. Wintertime hygroscopicity and volatility of ambient urban aerosol particles, Atmos. Chem. Phys., 18, 4533-4548, doi:10.5194/acp-18-4533-2018

Fodor, N., Foskolos, A., Topp, C.F.E., Moorby, J.M., Pásztor, L., Foyer, C.H., 2018. Spatially explicit estimation of heat stress-related impacts of climate change on the milk production of dairy cows in the United Kingdom. PLoS One 13, 1-18. doi:10.1371/journal.pone.0197076

Foyer, C.H., Siddique, K.H.M., Tai, A.P.K., Anders, S., Fodor, N., Wong, F.L., Ludidi, N., Chapman, M.A., Ferguson, B.J., Considine, M.J., Zabel, F., Prasad, P.V.V., Varshney, R.K., Nguyen, H.T., Lam, H.M., 2018. Modelling predicts that soybean is poised to dominate crop production across Africa. Plant Cell Environ. 1-13. doi:10.1111/pce.13466

Gazdag, O., Takács, T., Ködöböcz, L., Krett, G., Szili-Kovács, T., 2018. Alphaproteobacteria communities depend more on soil types than land managements. Acta Agric. Scand. Sect. B - Soil Plant Sci. doi:10.1080/09064710.2018.1520289

Gazdag, O., Takács, T., Ködöböcz, L., Mucsi, M., Szili-Kovács, T., 2018. Soil metabolic activity profiles of the organic and conventional land use at Martonvásár. Columella J. Agric. Environ. Sci. 5, 27-35. doi:10.18380/SZIE.COLUM.2018.5.1.27

Göndöcs, J., Breuer, H., Pongrácz, R., Bartholy, J., 2018. Projected changes in heat wave characteristics in the Carpathian Basin comparing different definitions. Int. J. Glob. Warm. 16, 119-135.

Juhász, A., Belova, T., Florides, C.G., Maulis, C., Fischer, I., Gell, G., Birinyi, Zs., Ong, J., Keeble-Gagnčre, G., Maharajan, A., Ma, W., Gibson, P., Jia, J., Lang, D., Mayer, K.F.X., Spannagl, M., Tye-Din, J.A., Appels, R., Olsen, O.A., 2018. Genome mapping of seed-borne allergens and immunoresponsive proteins in wheat. Sci. Adv. 4, 1-16. doi:10.1126/sciadv.aar8602

Kern, A., Barcza, Z., Marjanovic, H., Árendás, T., Fodor, N., Bónis, P., Bognár, P., Lichtenberger, J., 2018. Statistical modelling of crop yield in Central Europe using climate data and remote sensing vegetation indices. Agricultural and Forest Meteorology, 260-261, 300-320. doi:10.1016/j.agrformet.2018.06.009

Mesterházy, I., Mészáros, R., Pongrácz, R., Bodor, P., Ladányi, M., 2018. The analysis of climatic indicators using different growing season calculation methods - an application to grapevine grown in Hungary. Időjárás - Q. J. Hungarian Meteorol. Serv. 122, 217-235. doi:10.28974/idojaras.2018.3.1

Szatmári, G., Pásztor, L., 2018. Comparison of various uncertainty modelling approaches based on geostatistics and machine learning algorithms. Geoderma 337, 1329-1340. doi:10.1016/j.geoderma.2018.09.008

Webber, H., Ewert, F., Olesen, J.E., Müller, C., Fronzek, S., Ruane, A.C., Bourgault, M., Martre, P., Ababaei, B., Bindi, M., Ferrise, R., Finger, R., Fodor, N., Gabaldón-Leal, C., Gaiser, T., Jabloun, M., Kersebaum, K.C., Lizaso, J.I., Lorite, I.J., Manceau, L., Moriondo, M., Nendel, C., Rodríguez, A., Ruiz-Ramos, M., Semenov, M.A., Siebert, S., Stella, T., Stratonovitch, P., Trombi, G., Wallach, D., 2018. Diverging importance of drought stress for maize and winter wheat in Europe. Nat. Commun. 9, 1-10. doi:10.1038/s41467-018-06525-2

Salma, I., Németh, Z., 2019. Dynamic and timing properties of new aerosol particle formation and consecutive growth events. Atmos. Chem. Phys., 19, 5835-5852. doi:10.5194/acp-19-5835-2019

Measurements, observations

One of the main aims of the AgroMo project is the establishment of a complex experimental platform in Martonvásár. Implementation of the platform is finished. After data processing the main results will be presented here. Results of the 2017 measurements are available in the detailed documentation of the project [PDF file, ~11 MB; available only in Hungarian].


Technical documentation of the established eddy covariance sites is available here.


The research was funded by the Széchenyi 2020 programme, the European Regional Development Fund and the Hungarian Government (GINOP-2.3.2-15-2016-00028).